> Markdown version of [/jobs/ext/3550452-senior-nlp-developer](https://www.wearedevelopers.com/jobs/ext/3550452-senior-nlp-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior NLP Developer - **Company:** Artmac Soft LLC - **Location:** Prosper, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Transformation, Text Processing, Information Extraction, Python (Programming Language), Machine Learning, Language Modeling, Natural Language Processing, Named Entity Recognition, Tensorflow, Search Technologies, Sentiment Analysis, Pytorch, Retrieval-Augmented Generation, Large Language Models, Scikit Learn, HuggingFace, Document Classification, GPT, Natural Language Generation - **Published:** September 30, 2026 - **Apply:** https://www.careerjet.com/jobad/us4720d106051647144bc5a4990314c3cb ## About the Role * 8+ years of experience in NLP, Machine Learning, AI, * Strong proficiency in Python. * Strong hands-on experience with Natural Language Processing. * Experience with Transformers and Hugging Face. * Strong understanding of LLMs and language models. * Experience with text embeddings and semantic search. * Experience with Named Entity Recognition (NER), tokenization, text preprocessing, and information extraction. * Experience with fine-tuning, evaluating, and optimizing NLP and LLM models using appropriate evaluation metrics. * Experience developing RAG solutions. * Familiarity with PyTorch, TensorFlow, or Scikit-learn. * Design and develop advanced Natural Language Processing (NLP) solutions. * Develop NLP models for text classification, entity extraction, semantic search, sentiment analysis, document understanding, and text generation. * Work extensively with Transformer-based models and Large Language Models (LLMs). * Use Hugging Face Transformers and related libraries to develop and fine-tune language models. * Develop and optimize text embeddings for semantic search, similarity matching, and retrieval applications. * Design and implement RAG (Retrieval-Augmented Generation) pipelines. * Develop NLP pipelines for structured and unstructured text processing. Qualification: Bachelor's degree or equivalent combination of education and experience.